Simulation from sim_pDim_kCl()

View simulation

Cluster #1, level: a

column means:

##     V1     V2     V3     V4     V5     V6 
## 0.4642 0.2511 0.4557 0.5114 0.4700 0.4954

column ggcorr:

Cluster #2, level: c

column means:

##     V1     V2     V3     V4     V5     V6 
## 0.4432 0.7291 0.4188 0.5136 0.4487 0.4963

column ggcorr:

Cluster differneces; cluster 2 - cluster 1

column means:

##         V1         V2         V3         V4         V5         V6 
## -0.0209937  0.4779925 -0.0369365  0.0021539 -0.0212284  0.0008873

column ggcorr:

LDA

## Call:
## lda(dat, grouping = clas)
## 
## Prior probabilities of groups:
##      a      c      b 
## 0.3027 0.3947 0.3027 
## 
## Group means:
##       V1     V2     V3     V4     V5     V6
## a 0.4642 0.2511 0.4557 0.5114 0.4700 0.4954
## c 0.4432 0.7291 0.4188 0.5136 0.4487 0.4963
## b 0.4297 0.2675 0.4280 0.5104 0.4110 0.4682
## 
## Coefficients of linear discriminants:
##        LD1      LD2
## V1 -0.8696 -3.16249
## V2 13.0408  0.02112
## V3 -0.5433 -0.28177
## V4 -0.2805  1.69474
## V5 -0.7874 -4.52800
## V6 -2.6175 -0.77344
## 
## Proportion of trace:
##    LD1    LD2 
## 0.9972 0.0028

PCA

## Standard deviations (1, .., p=6):
## [1] 0.2620 0.2207 0.1612 0.1460 0.1414 0.1379
## 
## Rotation (n x k) = (6 x 6):
##        PC1     PC2     PC3      PC4     PC5      PC6
## V1 -0.1581  0.1947 -0.5195  0.15941  0.1468  0.78758
## V2 -0.8088 -0.5633  0.1180 -0.00358  0.1161  0.03388
## V3 -0.2292  0.5179  0.3255  0.37085  0.6419 -0.15413
## V4 -0.2039  0.2958 -0.2303 -0.85315  0.2640 -0.14253
## V5 -0.2976  0.4400  0.5252 -0.14619 -0.5678  0.31337
## V6 -0.3718  0.3090 -0.5305  0.29633 -0.4010 -0.48611

clSep; orig, orig vs MMP, MMp

Original variable cluster seperation:

Original vs MMP cluster seperation:

MMP cluster seperation:

As factors in the user study

Answer

PCA

Manual tour (radial)

Grand tour

Apendix

ClSep of Single-variable permutations (sim_pDim_kCl)